B.E. Electronics & Comm. Engg:Artificial Intelligence Techniques and Applications
Bachelor
In Patiala
Description
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Type
Bachelor
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Location
Patiala
Facilities
Location
Start date
Start date
Reviews
Course programme
First Year: Semester I
Mathematics I
Engineering graphics
Computer Programming
Physics
Solid Mechanics
Communication Skills
First year: Semester II
Mathematics II
Manufacturing Process
Chemistry
Electrical and Electronic Science
Thermodynamics
Organizational Behavior
Second year: Semester I
Numerical and Statistical Methods
Measurement Science and Techniques
Electromagnetic Fields
Semiconductor Devices
Signals and Systems
Digital Electronic Circuits
Human Values, Ethics and IPR
Second year: Semester II
Optimization Techniques
Analog Electronic Circuits
Networks and Transmission Lines
Electrical Engineering Materials
Analog Communication Systems
Data Structure and Information Technology
Environmental Studies
Third year: Semester I
Digital Signal Processing for Communications Microprocessors
VLSI Circuit Design
Digital Communication Systems
Microelectronics Technology
Linear Integrated Circuits and Applications
Summer Training(6 weeks)
Third year: Semester II
Project Semester
Project
Industrial Training(6 weeks)
Fourth year: Semester I
Antenna and Wave Propagation
Modern Control Engineering
Wireless and Mobile Communication Systems
Microwave Engineering
Engineering Economics
Fourth year: Semester II
Optical Communication Systems
Advanced Communication Systems
HDL Based Digital Design
Total Quality Management
Minor Project
Artificial Intelligence Techniques and Application
Overview of Artificial Intelligence: The concept and importance of AI, fields related to AI human intelligence vs machine intelligence
Knowledge and general Concepts: General concept of knowledge, Acquisition, Knowledge Representation and organization: Prepositional and Predicate Logic, Theorem Proving, Structured Knowledge representation using Semantic Networks, Frames, Scripts,, Conceptual Graphs, Conceptual Dependencies, Knowledge Manipulation: Search space control, Uninformed search, Depth first search, Breadth first search, Depth first search with iterative deepening, Heuristic Search :Minimax Search procedure
Expert Systems: Expert systems: advantages, disadvantages, Expert system architecture, functions of various parts, Mechanism and role of inference engine, Types of Expert system, Tuning of expert systems, Role of Expert systems in instrumentation and process control
Overview of AI languages
Artificial Neural Networks: History of neural networks, Structure and function of a single neuron, biological neurons, artificial neuron models, Types of activation functions, Neural network architectures: Fully connected, layered, acyclic, feed forward, Neural learning : correlation, competitive, evaluation of networks; Supervised learning: Back propagation algorithm, Unsupervised learning, winner-take all networks, adaptive resonance theory, Application areas of neural networks : classification, clustering, pattern associations, function approximation, forecasting.
Fuzzy Logic: Fuzziness vs probability, Crisp logic vs fuzzy logic, Fuzzy sets and systems, operations on sets, fuzzy relations, membership functions, fuzzy rule generation, de fuzzification, Applications of Fuzzy Logic in process Control and motion control
Genetic Algorithms: introduction and concept, coding, reproduction, cross-over and mutation Scaling, fitness, applications.
B.E. Electronics & Comm. Engg:Artificial Intelligence Techniques and Applications